Peripheralization Risk Mitigation: A Decision Support Model to Evaluate Urban Regeneration Programs Effectiveness

Roberto Gerundo, Antonio Nesticò, Alessandra Marra and Maria Carotenuto
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Roberto Gerundo: Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132-84084 Fisciano (SA), Italy
Antonio Nesticò: Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132-84084 Fisciano (SA), Italy
Alessandra Marra: Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132-84084 Fisciano (SA), Italy
Maria Carotenuto: Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132-84084 Fisciano (SA), Italy

Sustainability, 2020, vol. 12, issue 19, 1-19

Abstract: The term peripheralization indicates a process that can generate social, physical, and environmental degradation in urban areas. In the light of the new urban geography and the socio-economic trends taking place globally, there is a risk that the typical decay of a peripheral condition may affect city in their entirety, regardless of spatial proximity to its centre. Then, regeneration interventions should be targeted primarily at areas with a significant peripheralization risk, understood as a combination of potential degradation factors. Consequently, the decision-makers’ choice of the best design alternative should be informed by the knowledge of pre-existing vulnerability levels, and oriented towards the solution that maximizes their reduction. This is possible when the planning of interventions in the most vulnerable areas, through Urban Regeneration Programs, is able to take into account the results of the project alternatives economic evaluation. Such an approach constitutes the main novelty of the study. So, the aim of the work is to provide a decision support model for the evaluation of urban regeneration interventions effectiveness in areas of high peripheralization risk. To this end, the contribution defines a set of mitigation indicators and the assessment of the most effective design alternative through analytic hierarchy process (AHP). The proposed model was applied to an area of Marcianise Municipality, in Campania Region (Italy).

Keywords: peripheralization risk; mitigation indicators; analytic hierarchy process (AHP) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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